Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Engineering, Mathematics and Computer Science Journal (EMACS) Yayasan Cita Cendikiawan Al Khwarizmi
Zakiyyah, Alfi Yusrotis
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Pelatihan Peningkatan Tata Kelola Manajemen Sumber Daya Manusia Melalui Pembuatan Aplikasi di Puskesmas Sawah Besar di Jakarta Pusat Miranda, Eka; Kurniawati, Yulia Ery; Kusmiyati, Siti; Zakiyyah, Alfi Yusrotis; Aryuni, Mediana; Sano, Albert Verasius Dian
Dedikasi Sains dan Teknologi (DST) Vol. 5 No. 2 (2025): Artikel Pengabdian Nopember 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/dst.v5i2.7015

Abstract

Puskesmas Kecamatan Sawah Besar menghadapi kendala dalam mengelola data kehadiran karyawan. Kendala utama meliputi resiko kecurangan pencatatan data karena kurangnya pengawasan dan proses yang dilakukan masih secara manual. Kendala lain yang dialami Human Resource Development (HRD) dalam memantau kehadiran karyawan yaitu harus memindahkan data dari lembaran kertas ke komputer, hal ini rentan terhadap kesalahan memasukan data atau manipulasi data. Dari kendala yang dihadapi mitra maka kegiatan ini bertujuan untuk melakukan pelatihan peningkatan tata kelola manajemen sumber daya manusia melalui pembuatan aplikasi mobile yang informatif dan mudah diakses untuk meningkatkan kemapuan HRD mengelola data kehadiran karyawan. Aplikasi yang dibangun memuat fitur untuk mencatat dan mengelola kehadiran karyawan secara online dan dapat diakses melalui perangkat selular. Hasil kegiatan menunjukan adanya peningkatan tata kelola manajemen dan kemudahan pencatatan dan pengelolaan data kehadiran karyawan baik oleh karyawan itu sendiri maupun bagi HRD. Dengan penerapan teknologi digital yang optimal, Puskesmas Kecamatan Sawah Besar dapat memperbaiki efisiensi tata kelola sistem pencatatan kehadiran karyawan; meningkatkan transparasi; membantu HRD dalam memantau,  mengevaluasi kinerja karyawan dan mengambil keputusan secara lebih efisien dan cepat, dengan menyediakan informasi yang terintegrasi dan mudah diakses dari manapun.
Comparison of IndoBERT and SVM Algorithm to Perform Aspect Based Sentiment Analysis using Hierarchical Dirichlet Process Octarini, Sheila Prima; Zakiyyah, Alfi Yusrotis; Purwandari, Kartika
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 7 No. 3 (2025): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v7i3.13493

Abstract

Analyzing the performance of SVM and IndoBERT models for aspect-based sentiment analysis on fashion reviews in Tokopedia E-Commerce. This study employs the SMOTE technique due to the imbalance in the original data. Aspect determination using the Hierarchical Dirichlet Process (HDP) model yields satisfactory results with an adequate coherence score. The comparison between SVM and IndoBERT methods for aspect-based sentiment analysis shows that SVM is superior. IndoBERT achieved an accuracy of 87%, precision of 91%, recall of 93%, and F1-Score of 92%, while SVM attained an accuracy of 96%, precision of 100%, recall of 92%, and F1- Score of 96%. Therefore, the SVM model was chosen for implementation on a website that allows users to view aspect-based sentiment analysis on products in E-Commerce. The HDP model effectively grouped related terms into aspects such as “Material,” “Shipping,” and “Colour,” enhancing interpretability in sentiment classification. The resulting website enables users to analyze product sentiments interactively, providing actionable insights for both sellers and customers to assess product quality and service satisfaction more efficiently.
Co-Authors Aryuni, Mediana Eka Miranda, Eka Kusmiyati, Siti Octarini, Sheila Prima Purwandari, Kartika Sano, Albert Verasius Dian Yulia Ery Kurniawati